• Design, implement and maintain Python-based services for processing large volumes of time-series and event data.
• Build and extend internal simulation / analytics tools using Python (pandas, numpy, etc.).
• Develop and maintain integrations with internal and external APIs and data providers.
• Write clean, well-structured, well-tested code and documentation for the features you own.
• Collaborate with the founder and a junior analyst to translate ideas into robust, production-ready solutions.How We Work & What We Offer:
• High ownership: You will be a key Python developer for the core platform, with the opportunity to grow into a lead role as the team expands.
• Direct impact: You work directly with the founder; there is no long hierarchy between decisions and implementation.
• Lean, focused team: Minimal bureaucracy, clear priorities and room to shape the technical direction.
• Learning & growth: Strong exposure to both deep Python engineering and DevOps/infrastructure in a real production environment.
• Office & perks: Centrally located and well-equipped office (game & entertainment room, napping beds etc.).
• Food & comfort: Lunch, drinks, sweets and fruits are all provided by the company.
• Health: Private health insurance.

Working hours:

• You’ll be working 5 days a week from 10 a.m. to 7 p.m. (13:00-14:00 lunch time). Four days will be based in the office, and one day (Friday) you can work from home. 

Salary:

• Competitive and negotiable based on experience and knowledge, including a performance-based bonus package.

• 3+ years of experience building data-intensive or backend systems in Python.
• Strong knowledge of API design, integrations, and internal/external service communication.
• Solid computer science fundamentals, as system design, algorithms, data structures and complexity.
• Hands-on experience with pandas, numpy, and data manipulation for large datasets
  (experience with scipy, scikit-learn, statsmodels is a strong plus).
• Experience with relational & non-relational databases (e.g. MySQL/PostgreSQL, MongoDB).
• Practical experience with Docker, Linux-based servers, and deploying cloud services.
• Familiarity with Git/GitHub, Jira/Linear, and modern CI/CD workflows.
• Ability to independently own features end-to-end and deliver high-quality, well-tested code.
• At least technical English, ability to read and understand technical documentation. Verbal communication and written skills is a plus.

Nice to Have:

• Deep experience with the scientific Python stack (scipy, scikit-learn, statsmodels).
• Experience with Jenkins or more advanced DevOps tooling.
• Experience designing or operating distributed, high-availability systems.
• Background in statistics, time-series analysis, or risk / analytics systems.
• Familiarity with environments where correctness, reproducibility, and auditability are critical.

Application Guidelines:

Please submit your application through our Career Page link in the Apply for job button.

In the Cover Letter section, make sure to include:

• A brief note describing the relevant projects you have led or owned.
• (If available) links to your GitHub, portfolio, or any other supporting materials.

We look forward to reviewing your application!
Please be advised that only shortlisted candidates will be invited to the further stages of the recruitment process.